[Revealing the Cell Structure and Formation of Bamboo with Confocal Raman Microscopy].

Parenchyma cell (PAC), transition tissue between parenchyma cell and fiber cell (TC) and fibre cell (FC) of bamboo were studied by confocal Raman microscopy in this paper. Partial least squares regression was applied to establish a quantitative differentiation model for the three types of cells. The result showed that the determination coefficients (R²) of calibration and validation were respectively 0.810 and 0.800, and the root mean square error (RMSE) were respectively 0.323 and 0.332. What's more, three raman bands of 1,095, 1,319 and 1,636 cm⁻¹, verified to the characteristic peaks of pectin, hemicellulose and lignin, were found to be the important bands for the differentiation. Subsequently, these three raman bands were used to establish a multiple linear regression (MLR) model, and the determination coefficients (R²) of calibration and validation of the model were respectively 0.644 and 0.643, and the root mean square error (RMSE) were respectively 0.442 and 0.443. This result showed that there existed obvious difference among the three types of cells in these three raman bands. Finally, the raman spectral signal processed by wavelet transform to eliminate baseline were used to chemical imaging analysis. These results showed a rather large microfibril angle between cellulose fibrils and fibre axis, which contributed to higher modulus and hardness of cells. Hemicellulose and cellulose have similar distribution in the raman chemical image, due to the connection of hemicellulose and cellulose microfiber through hydrogen bond and the closely combination under the action of van der Waals force. The cell corners (CC) and compound middle lamella (CML) were heavily lignified, and a gradual decrease of lignification from the outer layer to the inner layer of the three cells indicate that lignification was first occurred at the CC and CML, and the lignification was not fully completed.

Spatio-temporal coupling analysis and tipping points detection of China's coastal integrated land-human activity-ocean system.

The coastal zone is typically highly developed and its ocean environment is vastly exposed to the onshore activities. Land-based pollution, as the "metabolite" of terrestrial human activities, significantly impacts the ocean environment. Although numerous studies have investigated these effects, few have quantified the interactions among land-human activity-ocean across both spatial and temporal scales. In this study, we have developed a land-human activity-ocean systemic framework integrating the coupling coordination degree model and tipping point to quantify the spatiotemporal dynamic interaction mechanism among the land-based pollution, human activities, and ocean environment in China from 2001 to 2020. Our findings revealed that the overall coupling coordination degree of the China's coastal zone increased by 36.9 % over last two decades. Furthermore, the effect of human activities on China's coastal environment remained within acceptable thresholds, as no universal tipping points for coastal pollution or ocean environment has been found over the 20-year period. Notably, the lag time for algal blooms, the key indicator of ocean environment health, was found to be 0-3 years in response to the land economic development and 0-4 years in response to land-based pollution. Based on the differences in spatiotemporal interactions among land-human activity-ocean system, we employed cluster analysis to categorize China's coastal provinces into four types and to develop appropriate management measures. Quantifying the interaction mechanism within the land-human activity-ocean system could aid decision-makers in creating sustainable coastal development strategies. This enables efficient use of land and ocean resources, supports coastal conservation and restoration efforts, and fosters effective management recommendations to enhance coastal sustainability and resilience.